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Combinatorial Optimization Jobs in California (NOW HIRING)

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Combinatorial Optimization information

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$41K

$140.6K

$198.4K

How much do combinatorial optimization jobs pay per year?

As of Aug 9, 2026, the average yearly pay for combinatorial optimization in California is $140,595.00, according to ZipRecruiter salary data. Most workers in this role earn between $116,900.00 and $164,300.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a combinatorial optimization specialist?

To thrive as a Combinatorial Optimization Specialist, you need a solid background in mathematics, computer science, and operations research, often supported by an advanced degree in a related field. Familiarity with programming languages (such as Python, C++, or Java), optimization libraries, and mathematical modeling tools like CPLEX or Gurobi is typically required. Strong analytical thinking, problem-solving skills, and effective communication help you devise and explain complex solutions to stakeholders. These skills are crucial for developing efficient algorithms and models that address challenging optimization problems in various industries.

How does a combinatorial optimization specialist typically collaborate with other departments within an organization?

Combinatorial Optimization specialists frequently work cross-functionally, partnering with data scientists, software engineers, and business analysts to translate complex business problems into mathematical models. They help teams identify optimal solutions for scheduling, routing, resource allocation, and other operational challenges. Effective communication is crucial, as specialists must explain complex algorithms to non-technical stakeholders and integrate their solutions into broader business processes. Collaborative teamwork and iterative problem-solving are common in this role.

What is the difference between Combinatorial Optimization vs Data Analyst?

AspectCombinatorial OptimizationData Analyst
Required CredentialsMathematics, Operations Research, Computer Science degreesStatistics, Data Science, Business Analytics degrees
Work EnvironmentResearch labs, consulting firms, tech companiesCorporate offices, finance, marketing departments
Industry UsageLogistics, manufacturing, AI, supply chainFinance, marketing, healthcare, retail

While both roles involve analytical skills, Combinatorial Optimization focuses on solving complex mathematical problems to find optimal solutions, often in logistics and operations. Data Analysts interpret data to inform business decisions, working across various industries. Understanding these differences helps clarify career paths and employer expectations.

What is combinatorial optimization?

Combinatorial optimization is a field in mathematics and computer science focused on finding the best solution from a finite set of possible solutions. It involves problems where you need to arrange, select, or group discrete objects according to certain rules to achieve an optimal outcome. Examples include scheduling, routing, and assignment problems. Techniques such as linear programming, branch and bound, and heuristics are often used to solve these problems. Combinatorial optimization is widely applied in logistics, operations research, computer science, and engineering.
What are popular job titles related to Combinatorial Optimization jobs in California? For Combinatorial Optimization jobs in California, the most frequently searched job titles are:
What job categories do people searching Combinatorial Optimization jobs in California look for? The top searched job categories for Combinatorial Optimization jobs in California are:
What cities in California are hiring for Combinatorial Optimization jobs? Cities in California with the most Combinatorial Optimization job openings:
Infographic showing various Combinatorial Optimization job openings in California as of July 2026, with employment types broken down into 84% Full Time, 11% Part Time, 1% Temporary, and 4% Contract. Highlights an 81% Physical, 4% Hybrid, and 15% Remote job distribution, with an average salary of $140,595 per year, or $67.6 per hour.

Senior / Principal AI Engineer for Business Intelligence (7063)

TSMC

San Jose, CA • Hybrid

$143K - $198K/yr

Full-time

Re-posted 9 days ago


TSMC rating

8.0

Company rating: 8.0 out of 10

Based on 21 frontline employees who took The Breakroom Quiz

57th of 156 rated electronics manufacturers


Job description

Overview of Role

As a Sr./Principal AI Engineer within TSMC's Artificial Intelligence for Business Intelligence Innovation (AI4BII) Center, you will join an exciting global team dedicated to generating crucial business intelligence insights that shape TSMC's strategic decisions and global operations. This role uniquely blends applied research with end-to-end product development, placing you at the forefront of our mission to leverage advanced AI for a competitive edge.

Operating with the agility of an internal startup, you will have the autonomy to build foundational systems from the ground up. You will tackle complex challenges spanning from advanced analytics and multimodal AI agents to time-series forecasting and reinforcement learning for manufacturing optimization. This is a role for a builder and a researcher who has been through the "zero-to-one" product journey and thrives on rapid iteration, technical leadership, and seeing their work create tangible business impact. Our hybrid work schedule currently requires 4 days in the office, ensuring a dynamic and collaborative work environment.

Responsibilities

  • Lead System Architecture: Own the end-to-end design and development of new AI-native products and platforms, from initial concept and data pipelines to scalable, production-grade services.
  • Build with Frontier AI: Drive the hands-on implementation of advanced AI systems leveraging frontier LLM models, including the design of robust Retrieval-Augmented Generation (RAG) pipelines and multi-agent workflows.
  • Prototype and Validate: Lead rapid validation sprints to build proof-of-concepts, create evaluation harnesses to measure accuracy, latency, and cost, and partner with product teams to harden prototypes for production release.
  • Engineer for Scale: Architect and implement the underlying MLOps infrastructure, including model serving, automated testing, and observability, to ensure our AI services meet enterprise-grade SLAs.
  • Drive Innovation: Research and validate novel AI use cases (e.g., threat-hunting copilots, developer productivity tools, automated workflow optimization) and build the foundational frameworks to accelerate their deployment.
  • Collaborate and Mentor: Partner closely with Product, Design, and business stakeholders to ensure solutions are technically sound and commercially impactful. Mentor junior engineers and foster a culture of experimentation, responsible AI, and first principles thinking.
  • Communicate Vision: Craft and deliver compelling executive-level narratives, demos, and visualizations that clearly communicate technical strategy, roadmaps, trade-offs, and business impact.

Minimum Qualifications

  • Experience: At least 10+ years of professional experience in software engineering, machine learning engineering, or related fields in high-performance environments. This should include:
    • 7+ years of hands-on experience in professional software and/or machine learning engineering.
    • 3+ years of experience in a technical leadership role, specifically focusing on architecting and building scalable systems powered by Generative AI or Large Language Models (LLMs).
  • Technical Expertise:
    • Generative AI & LLMs: Deep, hands-on expertise in the modern AI stack, including RAG, fine-tuning, agentic frameworks, prompt engineering, vector databases, and model evaluation techniques.
    • Backend & Systems Design: Strong fundamentals in backend engineering and distributed systems. Mastery of Python is required.
    • MLOps & Cloud: Hands-on experience with at least one major cloud AI platform (GCP Vertex AI, AWS SageMaker, Azure ML) and containerized workflows (Docker, Kubernetes).
  • Leadership & Communication:
    • Demonstrated ability to translate ambiguous business problems into clear technical blueprints and phased execution plans.
    • Exceptional communication and presentation skills, with experience conveying complex technical concepts to both engineering teams and senior management audiences.
  • Education:
    • B.S. or higher in Computer Science, Engineering, Mathematics, or a related technical field. An M.S. or Ph.D. is a plus.

Preferred Qualifications

  • Experience deploying AI into developer tooling (IDE plug-ins, CI/CD pipelines).
  • Active contributions to open-source AI/ML projects or publications in top-tier academic conferences.
  • A broad knowledge of mathematical modeling beyond ML, such as combinatorial optimization or operations research.

Company Description

As a trusted technology and capacity provider, TSMC is driven by the desire to be:

  • The world's leading dedicated semiconductor foundry
  • The technology leader with a strong reputation for manufacturing excellence
  • Advancing semiconductor manufacturing innovations to enable the future of technology

TSMC pioneered the pure-play foundry business model when it was founded in 1987 and has been the world's leading dedicated semiconductor foundry ever since. The Company supports a thriving ecosystem of global customers and partners with the industry's leading process technologies and a portfolio of design enablement solutions to unleash innovation for the global semiconductor industry. With global operations spanning Asia, Europe, and North America, TSMC serves as a committed corporate citizen around the world.

In North America, TSMC has a strong sales and service organization that works with customers by helping them achieve silicon success with cutting-edge technologies and manufacturing excellence. The Company has continued to accelerate its R&D investment and staffing in recent years and is expanding its manufacturing footprint to support customer innovation with 3D IC technologies and optimal manufacturing capacity.

Diversity statement

TSMC Technology, Inc. is committed to employing a diverse workforce and provides Equal Employment Opportunity for all individuals regardless of race, color, religion, gender, age, national origin, marital status, sexual orientation, gender identity, status as a protected veteran, genetic information, or any other characteristic protected by applicable law.

TSMC is an equal opportunity employer prizing diversity and inclusion. We are committed to treating all employees and applicants for employment with respect and dignity. If you require reasonable accommodation due to a disability during the application or the recruiting process, please feel free to notify us at g_accommodations@tsmc.com. TSMC confirms to all applicants its commitment to meet TSMC's obligations under applicable employment law. Reasonable accommodations will be determined on a case-by-case basis. 

Pay Transparency / Benefits statement

At TSMC, your base pay is only part of your overall total compensation package. At the time of this posting, this role typically pays a base salary between $123,240 and $200,000 per year. The range displayed reflects the minimum and maximum target for new hires. Actual pay may be more or less than the posted range. Factors that influence pay include the individual's skills, qualifications, education, experience and the position level and location.  TSMC's total compensation package consists of market competitive pay, allowances, bonuses, and comprehensive benefits. We also offer extensive development opportunities and programs.


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